Package: ecochange
Type: Package
Title: Integrating Ecosystem Remote Sensing Products to Derive EBV
        Indicators
Version: 2.2
Date: 2021-08-25
Authors@R: 
    c(person(given = "Wilson",
             family = "Lara Henao",
             role = c("aut", "cre"),
             email = "wilarhen@gmail.com"),
      person(given = "Victor",
             family = "Gutierrez-Velez",
             role = "aut"),
      person(given = "Ivan",
             family = "Gonzalez",
             role = "aut"),
      person(given = "Maria C.",
             family = "Londono",
             role = "aut"))
Maintainer: Wilson Lara Henao <wilarhen@gmail.com>
Description: Essential Biodiversity Variables (EBV) are state variables with dimensions on time, space, and biological organization that document biodiversity change. Freely available ecosystem remote sensing products (ERSP) are downloaded and integrated with data for national or regional domains to derive indicators related to structural EBV, including horizontal ecosystem extents, fragmentation, and information-theory indices. To process ERSP, users must provide at least a region of interest (polygon or geographic administrative data map). Downloadable ERSP include Global Surface Water (Peckel et al., 2016) <doi:10.1038/nature20584>, Forest Change (Hansen et al., 2013) <doi:10.1126/science.1244693>, and Continuous Tree Cover data (Sexton et al., 2013) <doi:10.1080/17538947.2013.786146>. The package relies on GDAL binaries. To instal GDAL in different operative systems, see the system-dependencies vignette.
License: GPL-3
Depends: R (>= 3.5.0), raster, rgeos, stats, ggplot2, sf, gdalUtils
Imports:
        readr,rgdal,parallel,curl,gdalUtilities,graphics,rvest,landscapemetrics,sp,tibble,utils,xml2,dplyr,R.utils,httr,getPass,methods,rlang,forcats,lattice,rasterDT,data.table,viridis
Suggests: knitr, rmarkdown, rasterVis
SystemRequirements: GDAL binaries
VignetteBuilder: knitr
Encoding: latin1
NeedsCompilation: no
Packaged: 2021-08-25 22:59:00 UTC; wilar
Author: Wilson Lara Henao [aut, cre],
  Victor Gutierrez-Velez [aut],
  Ivan Gonzalez [aut],
  Maria C. Londono [aut]
Repository: CRAN
Date/Publication: 2021-09-08 13:10:02 UTC
